update stoploss_from_open examples to use helper function

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Brook Miles 2021-03-18 09:47:03 +09:00
parent ce1ed76269
commit 983c0ef118

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@ -181,17 +181,9 @@ class AwesomeStrategy(IStrategy):
#### Calculating stoploss relative to open price #### Calculating stoploss relative to open price
Stoploss values returned from `custom_stoploss` always specify a percentage relative to `current_rate`. In order to set a stoploss relative to the *open* price, we need to use `current_profit` to calculate what percentage relative to the `current_rate` will give you the same result as if the percentage was specified from the open price. Stoploss values returned from `custom_stoploss()` always specify a percentage relative to `current_rate`. In order to set a stoploss relative to the *open* price, we need to use `current_profit` to calculate what percentage relative to the `current_rate` will give you the same result as if the percentage was specified from the open price.
This can be calculated as: The helper function [`stoploss_from_open()`](strategy-customization.md#stoploss_from_open) can be used to convert from an open price relative stop, to a current price relative stop which can be returned from `custom_stoploss()`.
``` python
def stoploss_from_open(open_relative_stop: float, current_profit: float) -> float:
return 1-((1+open_relative_stop)/(1+current_profit))
```
For example, say our open price was $100, and `current_price` is $121 (`current_profit` will be `0.21`). If we want a stop price at 7% above the open price we can call `stoploss_from_open(0.07, 0.21)` which will return `0.1157024793`. 11.57% below $121 is $107, which is the same as 7% above $100.
#### Trailing stoploss with positive offset #### Trailing stoploss with positive offset
@ -201,9 +193,7 @@ Use the initial stoploss until the profit is above 4%, then use a trailing stopl
``` python ``` python
from datetime import datetime, timedelta from datetime import datetime, timedelta
from freqtrade.persistence import Trade from freqtrade.persistence import Trade
from freqtrade.strategy import stoploss_from_open
def stoploss_from_open(open_relative_stop: float, current_profit: float) -> float:
return 1-((1+open_relative_stop)/(1+current_profit))
class AwesomeStrategy(IStrategy): class AwesomeStrategy(IStrategy):
@ -237,9 +227,7 @@ Instead of continuously trailing behind the current price, this example sets fix
``` python ``` python
from datetime import datetime from datetime import datetime
from freqtrade.persistence import Trade from freqtrade.persistence import Trade
from freqtrade.strategy import stoploss_from_open
def stoploss_from_open(open_relative_stop: float, current_profit: float) -> float:
return 1-((1+open_relative_stop)/(1+current_profit))
class AwesomeStrategy(IStrategy): class AwesomeStrategy(IStrategy):
@ -290,7 +278,7 @@ class AwesomeStrategy(IStrategy):
# using current_time directly (like below) will only work in backtesting. # using current_time directly (like below) will only work in backtesting.
# so check "runmode" to make sure that it's only used in backtesting/hyperopt # so check "runmode" to make sure that it's only used in backtesting/hyperopt
if self.dp and self.dp.runmode.value in ('backtest', 'hyperopt'): if self.dp and self.dp.runmode.value in ('backtest', 'hyperopt'):
relative_sl = self.custom_info[pair].loc[current_time]['atr] relative_sl = self.custom_info[pair].loc[current_time]['atr']
# in live / dry-run, it'll be really the current time # in live / dry-run, it'll be really the current time
else: else:
# but we can just use the last entry from an already analyzed dataframe instead # but we can just use the last entry from an already analyzed dataframe instead